Papers

Space-based solar radiation management has been proposed as a direct means of modulating Earth's radiative balance by reducing incident solar flux. A prominent concept consists of large sunshades operating near the Sun-Earth L1 region. However, feasibility is constrained by a fundamental lower bound on the required mass, arising from the coupled requirements of achieving sufficient insolation reduction while maintaining dynamical equilibrium under solar radiation pressure (SRP). We introduce a class of sunshades, termed deflective, designed to shape the effective SRP through macroscopic surface geometry. By employing inclined reflective elements, these systems redirect incident radiation to simultaneously control flux attenuation and the resulting momentum exchange, enabling the use of conventional high-reflectivity materials (e.g., aluminium films). The concept admits multiple geometrical realizations, including conical, pyramidal, and louvered (venetian-blind) configurations. A conical configuration is then studied in more detail as a representative implementation of this broader design principle. To improve its packaging efficiency and scalability, we consider a distributed constellation of units and propose a flat-folding strategy based on a Miura-Ori pattern adapted to the conical geometry finding its optimal configuration parameters resulting in a favourable geometry.

Exogenous interventions, including economic incentives, can be used to promote behavioral change and the adoption of new products or practices. They may act on different levels, either directly affecting customers' behavior (expressed level) or changing intentions (private level). The key question is which intervention strategy is more effective: targeting the expressed or the private level. Although expressed-private opinion (EPO) models are especially suitable for addressing this problem, they have not yet been used in this context. To fill this gap, we extend previous agent-based EPO models by incorporating exogenous interventions and compare different intervention strategies. We analyze the resulting model using a mean-field approximation, complemented by Monte Carlo simulations on a complete graph. Our results show that there is no universal answer to whether an intervention should target the expressed or the private opinion. The effectiveness of an intervention depends on the adoption level at the moment of its introduction. Interventions acting on the expressed level are more effective when adoption is still low, whereas interventions acting on the private level are more effective when adoption is already high and the goal is to support internal acceptance and reduce dissonance. Moreover, the model shows that high adoption is accompanied by low dissonance between expressed and private opinions, which is consistent with self-congruity theory. This agreement provides theoretical support for the model and strengthens its policy implications.

In a quark-gluon plasma (QGP) that is both dense and dissipative, do static color screening and thermodynamic response follow the same medium scale? The question matters because heavy-quark observables are routinely used to infer QGP properties, yet in a background with only finite density, or only momentum relaxation, the two scales cannot be compared: one of them is absent. We use the Einstein-Maxwell-axion geometry, in which the chemical potential $\mu$ and the translational-symmetry-breaking parameter $\beta$ enter as independent controls, to carry out this comparison at fixed temperature. The static potential, the thermal free energy, and the running coupling are computed with high numerical precision, and the zero-temperature limit is used to isolate the non-thermal response. The comparison reveals a hierarchy that is invisible when either scale is studied alone: $\mu$ controls the potential and the running coupling through near-horizon color screening, while $\beta$ controls the thermal free energy through its imprint on horizon entropy. At $T=0$ the hierarchy persists in the dissociation scale, where finite density shortens the binding range far more efficiently than pure momentum relaxation. The geometric origin is that the $\mu^2 z^4$ term grows toward the horizon and deforms the region that governs string screening, whereas the constant $\beta^2$ term shifts the horizon entropy without a comparable localized deformation. This separation yields a criterion for identifying which medium scale is at work in any holographic construction that contains both density and dissipation.

We identify the limit free energy of all multi-species spin glasses with centered $\pm 1$ spins. The result was previously known only under a convexity assumption on the covariance function of the Hamiltonian. We also obtain a one-species reduction of the formula for balanced multi-species models.

We study the dynamics of a d-level quantum system coupled to a bosonic reservoir when the coupling constant is large. It is known that in the limit of infinite coupling strength, the system undergoes an instantaneous nonselective measurement, resulting in the immediate decoherence in the measurement basis, followed by a unitary Zeno dynamics. Here we resolve this dynamical process by introducing a fine grained scaling regime of short times proportional to the inverse coupling. We provide a rigorous derivation of the open system dynamics in this regime of ultrastrong coupling and demonstrate how decoherence unfolds continuously in the new time scale. We show that Markovian dynamics which are not given by semigroups arise naturally, in contrast to what happens in the weak coupling theory.

Hybridization of internal and external atomic degrees of freedom in a Kasevich-Chu interferometer enables the possibility to enhance the sensitivity significantly even under quantum-standard limit. By introducing motional squeezing state as an input, we systematically derive the computational framework of quantum and classical Fisher information of two measurement protocols for arbitrary strength of Doppler effects. Through maximizing the corresponding classical Fisher information, we obtain the optimal control parameters and the corresponding quantum Fisher information. For population measurement, the largest sensitivity can be as large as four times than the semi-classical limit through enlarging the atom coherence length. For joint measurement of population and position, the competition between quantum enhancement and Doppler suppression induces two three behaviors, in one regime, the quantum enhancement dominates even in presence of strong Doppler broadening effects where the sensitivity is significantly enhanced; while in another regime, an optimal squeezing parameter is observed where the classical Fisher information reaches the maximum. Our results clearly demonstrate the robustness of external quantum enhancement against Doppler suppression. Our proposal can be readily applied to gravimeter of mobile platform where decoherence from noise will damage the many-body entanglement of internal spin squeezing.

This proceedings contribution summarizes the main results of the original paper arXiv:2506.18988. Cascading RG flows are characteristic of $\mathcal{N}=1$ gauge theories realized by D3-branes probing singularities in the presence of fractional branes. A celebrated example is the Klebanov-Strassler model, which exhibits an infinite cascade that ends with confinement. In this work, we explore a related setup where the addition of an orientifold plane modifies the cascade structure: the RG flow now consists of a finite number of steps, originating from a UV fixed point with a finite number of degrees of freedom. We provide a supergravity solution dual to this flow, that reproduces all its salient features.

I examine how the longitudinal light-front wave function of a meson encodes forward energy-momentum tensor (EMT) structure and the diagonal part of an off-forward generalized parton distribution in the large-$N_c$ 't~Hooft model. Light-light, equal-mass reference, heavy-light, and heavy-heavy systems are compared through their momentum distributions, differential entropy, bilocal Coulomb kernel, and forward mass-squared decomposition. An independent sine-basis calculation confirms the light-light spectrum despite the slow convergence of the sine representation. For equal constituent masses, the second moment obtained from the exact diagonal overlap has no term linear in the asymmetric skewness variable $b$, while its regular $b^2$ and $b^3$ coefficients are equal and determined by a universal kinematic contribution and a weighted wave-function gradient norm. At the equal-mass reference point, corresponding to $\beta=1/2$, the boundary expansion becomes resonant and generates a $b^4\ln^2(1/b)$ nonanalyticity, identifying the precise limitation of the diagonal two-body overlap. The companion Part II analysis constructs the ERBL completion required to cancel this support-dependent nonanalyticity and restore the analyticity of the local EMT moment.

Quantum computation has attracted numerous attentions and develops rapidly in the recent decades. To against the decoherence and the control errors upon the qubits, quantum error corrections are adopted. Such approaches require lots of redundant qubits, accurate measurement and timely feedback. Here we investigate a new framework of quantum computation that is associated with fuzzy processing. It will benefit significantly from three aspects: the fuzzy recognition of qubit states reduce the required gate fidelity; the fuzzy encoding encodes the information of the qubits into a distribution of probability, suppressing the fluctuations in the output of long quantum circuits; the fuzzy feedback offers a more efficient way to control the qubits when precision information of quantum states are absent. Furthermore, the fuzzy processing can be integrated into quantum error correction, eliminating the need for immediate correction operations. The proposed scheme will be fairly suitable for the solution of decision problems, which has significant applications in the optimization problems and control problems.

We investigate interaction-induced symmetry breaking in moiré superlattices created by twisting two identical materials where the electronic low-energy degrees of freedom reside in the vicinity of the $M$ points. Based on general symmetry arguments, we identify and classify the possible candidate instabilities that, besides flavor polarized states, also involve a variety of intervalley-coherent (IVC) orders. This complexity is related primarily to the presence of three valleys, instead of the well-studied scenario of two, e.g., in graphene: IVC states can couple all three valleys identically, with a non-trivial sign structure, or even with different magnitudes. We study the energetics using an analytical strong-coupling framework and unrestricted Hartree-Fock applied to the full continuum model, with very good agreement between the two approaches. Interestingly, depending on stacking, IVC instabilities not only appear due to superexchange at moderate bandwidths, but also deep in the strong-coupling regime as a result of deviations from the flat-metric condition. Our work demonstrates that twisted $M$-point materials provide a rich playground for complex correlated physics and highlights differences and similarities to twisted multilayer graphene.

Sycophancy in LLMs is documented across 70+ papers, but expert agreement on construct boundaries remains low (ICC=.184; Ye et al., 2026). The construct fragments because behavioral classification depends on which surface form is privileged. We adopt a materials-science framing: conversation as test specimen under load, LLM-model as material charge, pushback as progressive load, stance-flip as material failure. We characterize this failure across three loading cases (debate n=1000; false-presuppositions n=3400; ethical-setting n=3400; 10-17 material charges per case; 7800 specimens total) using 14 turn-level axis-measurements spanning velocity, damage accumulation, frame-drift, brittleness, and direction stability, plus three speaker-resolved axes from an independent pipeline. The measurements are Hooke-coupled ($\sigma = E \cdot \varepsilon$ analog) and reproduce across loading cases with effects up to $|r_{rb}| = 0.35$ on debate; the sign structure adds a second pattern: the ethical-setting case inverts the velocity and accumulation blocks. Variance composition partitions into two profiles: debate is charge-dominated (brittle-fracture-like: the material grade decides), false-presuppositions and ethical-setting are topic-dominated (creep-like: the load decides); the ratios (2.03 vs 0.13/0.17) are estimator-dependent, for debate even in direction. Cross-judge reliability (GPT-4o vs Haiku 4.5) shows debate scoring is judge-robust (Cohen's $\kappa = 0.88$) while false-presupposition scoring is judge-sensitive ($\kappa = 0.36$) – a caveat single-judge benchmarks must report. This is the methodological move Ye et al.'s diagnosis calls for: a multi-axis characterization that does not depend on which surface form of the construct one privileges.

We present a novel device for the inline activity monitoring of gaseous tritium, named Gaseous Tritium Activity Monitoring with Scintillators (GaTAMOS). Unlike established methods that often rely on liquid scintillation or plastic scintillators with limited chemical resistance, this system utilises a chemically inert, inorganic Terbium-activated Gadolinium Oxysulfide (Gd2O2S:Tb) ceramic. A specialised soldering technique was developed to join the ceramic scintillator to a stainless-steel flange, achieving a vacuum-tight seal fully compatible with high-purity tritium applications. The device was characterised using pure tritium gas, demonstrating a linear response and high sensitivity across a dynamic range from < 1 kBq to >10 GBq. A key advantage of the ceramic material over organic alternatives is its high tolerance to aggressive cleaning agents. We demonstrate that the inevitable tritium memory effect can be significantly mitigated by flushing the cell with ethanol, removing >95% of residual contamination within minutes. The proposed system offers a compact, robust, and cost-effective alternative to ionisation chambers or BIXS systems for process monitoring in tritium handling facilities.

Living cells utilize condensates to spatially concentrate molecules in response to dynamic signals. For instance, nuclear condensates respond to oscillations in transcription factor levels in the nucleoplasm, including those involved in repairing multiple DNA breaks. To understand how oscillating signals affect condensates, we analyze a theoretical model using numerical simulations and analytical theory. While passive dynamics would drive all molecules into a single condensate, we find that sufficiently fast oscillations stabilize multiple droplets, allowing control of their sizes. We thus reveal a new behavior of chemically active droplets, which could be exploited in synthetic applications.

Conventional elements play an integral role in measuring time. Clocks unavoidably require a chosen standard of synchrony. The periodic process selected for the standard is not imposed upon us in any way. Conventionalism, in this regard, offers an insightful perspective on temporal measurement. The strong formulation of this doctrine is, however, questionable. After elaborating on strong conventionalism, it will be argued that it has three downsides: (i) it fails to properly distinguish between highly stable natural processes and complete randomness, as periodicities differ in terms of regularity; (ii) it does not explain that a clock actually measures something, to wit, parts of its own path along its worldline in spacetime; (iii) and relatedly, it omits the distinction between a temporal interval as a physical quantity and the arbitrarily chosen unit of time, leaving the distinction between temporal quantities and units a mystery. This article does not claim that strong conventionalism is incorrect; rather, considering the critical arguments against it, we may conclude that it remains an incomplete theory of what clocks measure.

This work addresses the critical challenge of excited-state preparation for semiconductor band structure calculations. We introduce a variational adiabatic eigensolver (VAE) protocol that combines adiabatic evolution with variational optimization to prepare high-fidelity eigenstates on noisy intermediate-scale quantum (NISQ) devices. Applying a momentum-space truncation, we accurately compute the electronic band structure of silicon – an idealized infinite periodic system – using only a modest number of qubits. Our approach employs multi-qubit parameterized circuits and a phase-based loss function, overcoming limitations of conventional methods. These limitations include the circuit-construction difficulty in traditional adiabatic approaches and the reduced accuracy of variational quantum eigensolvers for excited states. Through rigorous numerical simulation and experimental implementation on a superconducting quantum processor, we successfully prepare silicon's valence-band and conduction-band eigenstates. Single-shot readout yields state fidelities exceeding 96%, and the measured energy expectations agree with theoretical band energies within 0.5 eV. Further refinement via single-frequency oscillation fitting reduces the energy deviation to below 0.01 eV. This framework provides a robust and practical pathway for precisely determining electronic structures in quantum materials.

Neural operator models trained on simulation data often lose accuracy when applied to experimental measurements due to the sim-to-real gap. Standard fine-tuning with limited real data can reduce this gap, but it may also damage the core physics-relevant representations learned during pretraining. Although knowledge-preserving adaptation has been widely investigated in vision or language tasks, it remains unclear whether these methods are suitable for neural operators whose architectures and protected knowledge are fundamentally different. Neural operators need to preserve core-scale physical structures rather than semantic or visual features. We propose PhysGuard, a physics-preserving framework for accurate sim-to-real adaptation of neural operators. Specifically, PhysGuard uses the empirical Fisher Information Matrix computed on simulation data to identify physics-critical parameter directions, then restricts fine-tuning updates to directions that do not interfere with them. A layer-wise Gram-matrix formulation makes this efficient for models with millions of parameters, while an adaptive threshold automatically determines the protected subspace size. A spectral probe experiment shows that the dominant Fisher directions are strongly associated with low-frequency output structures. Experiments on benchmark across four neural operator architectures and different physical systems show that PhysGuard performs strongly on most evaluation metrics compared to baselines. The benefits are most evident under severe domain shift, where it reduces low-frequency error by up to 32% compared to standard fine-tuning while maintaining adaptability. Our code is available at https://github.com/Data-Driven-Computational-Geotechnics/PhysGuard.

Owing to rapid recent progress, ultracold atomic lattice systems for simulating topological phases are now at a pivotal stage, evolving from established paradigms into increasingly versatile and programmable quantum simulators. In this review, we survey recent experimental advances across four major classes of platforms: optical lattices, including optical lattices with laser-assisted tunneling and optical Raman lattices; synthetic lattices in momentum or internal-state space; Floquet-engineered lattices; and optical tweezer arrays, all of which offer distinct capabilities for realizing and probing topological matter. For each class, we highlight representative experimental breakthroughs, the topological models that have been realized, and the advanced detection and characterization techniques employed, emphasizing how these complementary approaches collectively expand the frontier of quantum simulation. We also discuss emerging directions in strongly correlated and nonequilibrium topological phases, and conclude with an outlook on future prospects.

We investigate magnetotransport in a van der Waals heterostructure composed of monolayer graphene and the insulating helical antiferromagnet nickel iodide (NiI$_2$). While NiI$_2$ is highly resistive and thus poorly suited for direct transport measurements, we demonstrate that magnetotransport in an adjacent graphene layer provides an electrical readout of magnetic-state-dependent interfacial behavior. Most notably, first-harmonic longitudinal magnetoresistance under in-plane magnetic fields exhibits large, anisotropic low-field peaks that are absent from a monolayer graphene/h-BN control device and are suppressed above the multiferroic transition temperature of NiI$_2$. Temperature-dependent harmonic measurements provide complementary evidence: the second-harmonic resistance shows the clearest nonlinear contrast relative to the control device, while the third harmonic contains a larger generic nonlinear and thermal background that is nevertheless modified in the heterostructure. These results demonstrate that graphene-based transport measurements offer a sensitive, non-invasive probe of magnetic phase behavior in electrically insulating van der Waals magnets, opening routes toward spintronic devices based on insulating vdW multiferroics.

Designing spray nozzles requires predicting how geometry shapes transient two-phase breakup, but high-fidelity volume-of-fluid (VOF) simulations with adaptive mesh refinement (AMR) are too expensive for iterative design exploration. Standard surrogate models are also challenged by this setting because both the liquid–gas interface and the underlying adaptive discretization evolve across time and geometries. We introduce a geometry-conditioned latent surrogate trained on 797 two-phase nozzle simulations that addresses this by encoding the AMR cell-density field, rather than the full multi-channel flow state, as a compact proxy for where the solver concentrates resolution. From this representation, the model reconstructs transient density evolution and nozzle geometry, and a lightweight second stage recovers the remaining flow variables. On held-out simulations, the method accurately captures key interface dynamics while reducing inference time to 0.045 seconds per trajectory, corresponding to a speed-up of more than $6\times10^4$ relative to Basilisk CFD. These results suggest that AMR refinement structure can serve as a compact and learnable representation for geometry-conditioned surrogate modeling of transient two-phase flows.

We extend the entropy formula of Menon and Yu for the real Deep Linear Network (DLN) to its complex and quaternionic analogues, obtaining a unified formula for DLNs over $\mathbb{R}$, $\mathbb{C}$, and $\mathbb{H}$.

Deep neural networks (DNNs) have achieved remarkable success in scientific computing, yet they often suffer from spectral bias in capturing oscillatory and multiscale behaviors. In this study, we investigate this limitation by examining the failure of shallow ReLU neural networks in fitting high-frequency functions. This observation identifies two important factors in resolving rapid oscillations: the initial slope scale and the distribution of partition points induced by the networks. Motivated by this analysis, we propose RepNN, a reparameterized neural network model with ReLU or tanh activations designed for high-frequency and multiscale problems. The key idea is to reparameterize the weights and biases in the first hidden layer, which enables effective control of the initial slope scale and provides an appropriate distribution of the initial partition points. Furthermore, treating the reparameterized weights and biases as trainable parameters allows the DNN to achieve adaptive frequency scaling during training. In addition, we derive quantitative estimates for the output and slope magnitudes of the reparameterized DNN to guide the initialization of the proposed method. Numerical experiments, including multiscale one-, two-, and four-dimensional function approximations, forward and inverse PDE problems in combination with physics-informed neural networks (PINNs), and operator learning for an earthquake problem using real data, demonstrate that RepNN improves the predicted accuracy of vanilla DNNs in capturing highly oscillatory features. These results indicate that RepNN provides an effective and flexible approach for overcoming spectral bias and applying DNNs to multiscale problems.

We present a new class of interacting dark sector models in which the intrinsic entropy of a dark matter fluid couples to a scalar field describing dark energy. These interactions are constructed within a covariant Lagrangian framework, including algebraic and derivative entropy couplings, effectively leading to pure momentum exchange in the dark sector. A key feature is that the background cosmology remains unchanged and therefore indistinguishable from $\Lambda$CDM or uncoupled quintessence. However, at the level of the linear perturbations, the dark matter Euler equation exhibits scale-dependent contributions, while the continuity equation is unmodified. We show that these classes of models are compatible with current CMB constraints and can potentially produce observable signatures in large-scale structure.

The paper studies the Q-tensor model for nematic liquid crystals, a system that couples a Navier-Stokes equation with an evolution equation for the order parameter tensor Q. The first goal of the paper is to establish the local well-posedness of the system in $\mathbb R^N$ and $\mathbb R^N_+$ for $N=2,3$ in the $L^2$ framework, improving existing results in the literature, where the existence of local strong solutions was obtained only under smallness assumptions on the initial data. Fundamental is the application of the energy method, which shows a cancellation phenomena on the nonlinear terms, allowing the use of a contraction argument to prove existence and uniqueness of solutions. Finally, with the same approach we establish global well-posedness in the three-dimensional case for small initial data.

Quadrupolar excitons in van der Waals heterostructures - quantum superpositions of anti-aligned dipolar excitons - offer a novel platform to explore exotic many-body physics, with applications to quantum sensing and photonic devices. Yet their internal structure, symmetry, and real-space localisation remain largely unknown. Here, we reveal the atomic-scale structure of quadrupolar excitons in twisted WSe2/WS2/WSe2 trilayers by solving the Bethe-Salpeter equation within a large-scale atomistic framework. We discover that large atomic relaxations at small twist angles give rise to two distinct quadrupolar excitons trapped at moiré lattice sites, differing in the in-plane symmetry of the electron density about the hole: one azimuthally symmetric, with the density maximal at the hole, and one threefold symmetric, with a node at the hole. Moiré trapping, neglected in commonly used models of quadrupolar exciton formation, is critical to their many-exciton phases. Without moiré trapping, quadrupolar excitons transition into anti-parallel dipolar excitons on a bipartite square lattice, while with trapping, the same dipoles are confined to a triangular lattice and experience geometric frustration. Our study uncovers the highly non-trivial nature of quadrupolar excitons, with direct implications for simulating frustrated quantum magnetism in a fully tunable excitonic platform.

We demonstrate that the coherent synchrotron radiation (CSR) can be used for the scattering type near-field scanning optical microscopy (s-SNOM). Using a commercially available s-SNOM coupled to a synchrotron source we perform THz imaging and spectroscopy experiments in the spectral range of 25-55 cm-1 and spatial resolution of 60 nm. It is shown that the same optical configuration can be used for nanoscopy in the range of 25 to 4000 cm-1. Conducting experiments across the THz, far-, and mid-IR spectral ranges within a single setup offers a unique capability for the ultrabroadband characterization of complex materials in both life and material sciences at the nanoscale.

We consider complex-weighted graphs, whose edge weights belong to a sector in the complex plane. We show that the corresponding Dirichlet Laplacian is $m$-sectorial, and, hence, generates a contractive holomorphic $C_0$-semigroup. Further, it is shown that every sectorial complex-weighted graph can be extended to an electrical network, where by electrical networks we mean graphs, whose edge weights are holomorphic functions, arising from physical admittances. This result allows us to establish convergence results for the infinite complex-weighted graphs, e.g. convergence of solutions of Dirichlet problems and convergence of complex-valued capacities on a finite exhaustion. Finally, we define a recurrence for complex-weighted graphs, and, using the convergence results, give its characterizations in terms of functional spaces, capacity, Green's function, resolvents of the Dirichlet Laplacian and properties of the Neumann Laplacian.

The centre of the Milky Way (MW) hosts powerful multiphase outflows, as evidenced by the Fermi and eROSITA bubbles, and by cold atomic hydrogen (HI) gas clouds detected up to a few kiloparsecs above the disc. In this paper, we investigate the process of launching gaseous outflows in the nuclear region of our Galaxy from supernova feedback. Using the PIERNIK code, we perform a simulation of the Galaxy with 3 pc resolution in both the Central Molecular Zone (CMZ) and the surrounding outflows. Our model follows the entire gas dynamics, from accretion onto the central star-forming ring through the dust lanes to star formation, feedback and the launching of outflows. Star formation occurs in cycles of starbursts followed by quiescent periods, mainly driven by intermittent gas inflows along the dust lanes. Stellar feedback generates hot ($\sim 10^7$ K) winds launched from the CMZ at velocities of order 1000 km/s, as well as colder ($\sim 10^4$ K) Hi gas clouds with velocities of $\sim 100$ km/s at heights of 1 - 2 kpc from the mid-plane. The spatial distribution, kinematics, and masses of our simulated clouds are broadly consistent with observations. Their properties indicate that they are accelerated out of the disc by entrainment from the hot phase. At least 20% of these clouds return to the disc in fountain flows, while the majority are disrupted by interaction with the hot phase. While periods of intense star formation and supernova activity lead to more numerous outflowing clouds with higher masses and densities, quiescent phases with star formation rates close to that observed in the CMZ still produce Hi clouds consistent with data. These results suggest that stellar feedback alone, operating in a time-variable nuclear environment, can account for the observed population of cold clouds in the Galactic centre outflow.

Cryogenic hydrogen isotope fuel layers with high structural integrity and atomic-scale smoothness are prerequisites for symmetric implosion and ignition in inertial confinement fusion (ICF). Using deuterium (D$_2$) as model fuel, we perform large-scale molecular dynamics simulations with a Feynman-Hibbs corrected Silvera-Goldman potential to describe nuclear quantum effects at low temperatures, systematically investigating D$_2$ crystallization inside spherical ablator capsules. By varying substrate lattice constant from 3.1 angstrom to 3.9 angstrom, we demonstrate that lattice matching dictates the transition from coherent epitaxial growth to polycrystalline formation, establishing it as the primary design principle for high-performance targets. When the substrate lattice closely matches the equilibrium hexagonal-close-packed (HCP) spacing of cryogenic D$_2$ (approximately 3.5 angstrom), D$_2$ forms coherent layer-by-layer epitaxial growth consistent with Ostwald's stepwise nucleation theory, yielding HCP-dominated near-single crystals with minimal dislocations and ultra-smooth inner surfaces. In contrast, large lattice mismatch destabilizes coherent growth and causes island-like growth, producing polycrystalline structures with mixed HCP/FCC phases, elevated defects, and greatly increased surface roughness. Radial stress analysis shows that interfacial stress from mismatch localizes within 2-3 molecular layers near the interface, triggering subsequent defect-mediated growth. These findings highlight substrate lattice matching in regulating confined solid growth and crystallization quality, establish it as a key principle for ablator inner-surface engineering in ICF cryogenic targets, and offer atomic guidance for growing high-quality single-crystal deuterium-tritium (DT) fuel layers with optimal smoothness.

Many-qubit circuit states are hard to inspect directly, so they are often summarized by pairwise graph weights. Common pairwise weights report symmetric correlations, while many circuit questions are directed and basis-specific: if qubit $i$ is measured in a given basis, how strongly does the outcome reshape the conditional state of qubit $j$? We define $K_{i\to j}$, a directed, basis-conditioned edge weight for this question. It is large when the two measurement outcomes occur with comparable probability and leave qubit $j$ in clearly different conditional states; it is zero when the source outcome is deterministic or the target states are indistinguishable. The scalar uses standard binary-ensemble distinguishability; the paper's contribution is to turn this conditional comparison into a directed network layer for circuit states. The resulting networks are computable from two-qubit reduced density matrices. They are diagnostic (not entanglement measures): for pure two-qubit states $K$ reduces to the tangle $C^2$ (squared concurrence)~\cite{WoottersConcurrence,CKWTangle}, while separable mixed states can reach $K=1$. Examples on teleportation, Grover, QAOA, and random circuit families show the intended use: $K$-networks map feed-forward, phase, and interaction-graph structure that symmetric or computational-basis summaries can leave weak or absent.

The realization of fractional quantum Hall (FQH) states, characterized by fractional charge and intrinsic topological order, on quantum computers represents a central challenge at the interface of condensed matter physics and quantum information science. Current methods are grouped into two types: methods based on (quasi-)adiabatic evolution of complex parent Hamiltonians to yield target states, and circuit-based approaches for direct state preparation, which are confined to effectively one-dimensional systems near the thin cylinder or torus limit. We introduce a complementary scheme relying on direct quantum circuit construction, which works for arbitrary geometries. Specifically, we present a method to precisely prepare the $\nu=1/3$ Laughlin state on the sphere geometry and demonstrate that it significantly reduces the required number of two-qubit gates and circuit depth, compared to variational quantum circuit approaches. In addition, we employ optimal control techniques to design control pulses for both superconducting and Rydberg atom platforms, identifying experimentally feasible protocols for state preparation. Our results provide an efficient and hardware-relevant pathway for realizing generic FQH states on both noisy intermediate-scale and fault-tolerant quantum devices.